Processing Technology Based on Radar Signal Design and Classification

Ou, Jianping; Zhang, Jun; Zhan, Ronghui

doi:10.1155/2020/4673763

Cited by 17 publications

(4 citation statements)

References 168 publications

(208 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e antenna is an important part of radar, and the advancement of radar technology is inseparable from reliable and stable radar signals, which will directly affect the detection effect of radar [1]. However, the directivity of a single antenna is limited, to use antennas for electrical scanning in space, several antennas can be arranged together regularly to produce a directional pattern, which is called an antenna array [2].…”

Section: Introductionmentioning

confidence: 99%

Research on Quantization Error Influence of Millimeter-Wave Phased Array Antenna

Yang

Zhu

Xia

et al. 2021

International Journal of Antennas and Propagation

View full text Add to dashboard Cite

The millimeter-wave phased array antenna is a higher integration system that is composed of different subarray modules, and in actual engineering, the existing amplitude, phase errors, and structural errors will change the performance of the array antenna. This paper studies the influence of the random amplitude and phase errors of the antenna array in the actual assembly process and the actual position errors between the subarrays on the electrical performance of the antenna. Based on the planar rectangular antenna array-electromagnetic coupling model, we propose a method of verifying the effect of random errors on the phased array antenna. The simulation result shows that the method could obtain the critical value of the error generated by the antenna subarray during processing and assembly. To reduce the error factor, it is necessary to ensure that the random phase and amplitude error should not exceed 10 ° , 0.5 dB . The error in the X-direction during assembly should be ≤ 0.05 λ , and the error in the Y-direction should be ≤ 0.1 λ . When symmetrical deformation occurs, the maximum deformation should be less than 0.05 λ .

show abstract

Section: Introductionmentioning

confidence: 99%

Research on Quantization Error Influence of Millimeter-Wave Phased Array Antenna

Yang

Zhu

Xia

et al. 2021

International Journal of Antennas and Propagation

View full text Add to dashboard Cite

show abstract

“…Therefore, how to effectively and efficiently recognize LPI radar signals in complex electromagnetic environments is still a challenging task for electronic warfare systems [4][5][6]. Moreover, the utilization of low power, enhanced time-width products, frequency agility, composite modulation, and other associated technologies in LPI radar presents much more difficulties for signal recognition [7].…”

Section: Introductionmentioning

confidence: 99%

LPI Radar Signal Recognition Based on Feature Enhancement with Deep Metric Learning

Ren,

Quan,

Shen

et al. 2023

Electronics

View full text Add to dashboard Cite

Low probability of intercept (LPI) radar signals are widely used in electronic countermeasures due to their low power and large bandwidth. However, they are susceptible to interference from noise, posing challenges for accurate identification. To address this issue, we propose an LPI radar signal recognition method based on feature enhancement with deep metric learning. Specifically, time-domain LPI signals are first transformed into time–frequency images via the Choi–Williams distribution. Then, we propose a feature enhancement network with attention-based dynamic feature extraction blocks to fully extract the fine-grained features in time–frequency images. Meanwhile, we introduce deep metric learning to reduce noise interference and enhance the time–frequency features. Finally, we construct an end-to-end classification network to achieve the signal recognition task. Experimental results demonstrate that our method obtains significantly higher recognition accuracy under a low signal-to-noise ratio compared with other baseline methods. When the signal-to-noise ratio is −10 dB, the successful recognition rate for twelve typical LPI signals reaches 94.38%.

show abstract

“…Due to the rapid advancement in the field of radar technology, an increasing demand in radar has changed its role from attaining the azimuth, the distance, and altitude information to the receiving end of electromagnetic waves to obtain huge extensible content, like, displacement field of lander's earthquake mapped, hand-gesture recognition, and identifying pedestrians with multiple-input multiple-output (MIMO). 2,3 Radar technology has been largely utilized in real-time applications because of its certain properties, such as large bandwidth of signal and accurate time-width that improves the antijamming property of the signal. However, the stability and reliability of signals can be enhanced using the multidisciplinary needs, such as amplification, generation of signal, processing, reception, and detection.…”

Section: Introductionmentioning

confidence: 99%

“…However, the stability and reliability of signals can be enhanced using the multidisciplinary needs, such as amplification, generation of signal, processing, reception, and detection. 2,4 One of the prominent sensors that have been widely considered for indoor tracking is Ultra Wideband Radar (UWB), because it has the potential to limit the privacy issues. 5 IR-UWB radar is utilized to track moving objects by determining the time of arrival (TOA) of backscattered impulses, such as signal broadcasted by radar sensor and backscattered by moving object.…”

Section: Introductionmentioning

confidence: 99%

Visual features and Deep Maxout Network‐based moving target detection using radar signals under sea clutter

Battula

Jaya

2021

Int J Intell Syst

View full text Add to dashboard Cite

Radar echoes have emerged as a rapid technology that is utilized in a wide range of applications especially in target identification under sea-clutter background. The detection of moving targets under a sea-clutter background is still a complex task because of the entering and evacuating of targets, which is highly unpredictable and unexpectable. Because of the lack of essential information, target detection and parameter estimations have become key constraints. Besides, it is very difficult to differentiate directly the small targets from the clutter background. However, the accurate location of the target cannot be determined exactly by the existing approaches.To address such limitations, an efficient strategy is proposed in this study for recognizing the moving targets under sea-clutter background using the proposed Magnetic Ant Lion Optimization algorithm, which is derived by the integration of Magnetic Optimization and Ant Lion Optimization. However, the proposed method achieves effective performance in terms of detection rate, mean-squared error, and the missed target rate with the values of 0.988, 0.012, and 0.224 for vertical-horizontal polarity.

show abstract

Processing Technology Based on Radar Signal Design and Classification

Cited by 17 publications

References 168 publications

Research on Quantization Error Influence of Millimeter-Wave Phased Array Antenna

Research on Quantization Error Influence of Millimeter-Wave Phased Array Antenna

LPI Radar Signal Recognition Based on Feature Enhancement with Deep Metric Learning

Visual features and Deep Maxout Network‐based moving target detection using radar signals under sea clutter

Contact Info

Product

Resources

About